equal_propensity_estimator

For use with data from randomized experiments where treatments are known to
be randomly assigned.

An interface to the algorithms of 'Interpretable AI'
<https://www.interpretable.ai> from the R programming language.
'Interpretable AI' provides various modules, including 'Optimal Trees' for
classification, regression, prescription and survival analysis, 'Optimal
Imputation' for missing data imputation and outlier detection, and 'Optimal
Feature Selection' for exact sparse regression. The 'iai' package is an
open-source project. The 'Interpretable AI' software modules are proprietary
products, but free academic and evaluation licenses are available.

Jack Dunn

Interface to 'Interpretable AI' Modules

Ying Zhuo

Interpretable AI LLC 

equal_propensity_estimator function

<dl><dt>...</dt>
<dd>Use keyword arguments to set parameters on the resulting learner.
Refer to the Julia documentation for available parameters.</dd></dl>

Arguments

Requires IAI version 2.1 or higher.

IAI Compatibility

Learner that estimates equal propensity for all treatments. — equal_propensity_estimator

<dl>

<dt>...</dt>
<dd>Use keyword arguments to set parameters on the resulting learner.
Refer to the Julia documentation for available parameters.</dd>

</dl>

Requires IAI version 2.1 or higher.

equal_propensity_estimator: Learner that estimates equal propensity for all treatments.

Description

Usage

Arguments

IAI Compatibility

Details

Examples